Intelligent Control and Automation

Covers different topics from intelligent control and automation, including intelligent control methods, fuzzy control techniques, neural networks-based control, and intelligent control applications.
This book covers different topics from intelligent control and automation, including intelligent control methods, fuzzy control techniques, neural networks-based control, and intelligent control applications. Section 1 focuses on intelligent control methods, describing automatic intelligent control system based on intelligent control algorithm, intelligent multi-agent based information management methods to direct complex industrial systems, a design method of intelligent ropeway type line changing robot based on lifting force control and synovial film controller, and a summary of PID control algorithms based on AI-enabled embedded systems. Section 2 focuses on fuzzy control techniques, describing an adaptive fuzzy sliding mode control scheme for robotic systems, an adaptive backstepping fuzzy control based on type-2 fuzzy system, a fuzzy PID control for respiratory systems, a parameter varying PD control for fuzzy servo mechanism, and a robust fuzzy tracking control scheme for robotic manipulators with experimental verification. Section 3 focuses on neural networks-based control, describing neural network supervision control strategy for inverted pendulum tracking control, a neural PID control strategy for networked process control, a control loop sensor calibration using neural networks for robotic control, a feedforward nonlinear control using neural gas network, and a stable adaptive neural control of a robot arm. Section 4 focuses on intelligent control applications, describing ship steering control based on quantum neural network, a human-simulating intelligent PID control, an intelligent situational control of small turbojet engines, and a technical review of an antilock-braking systems (ABS) control.

Contributor: Jovan Pehcevski (Edited by)

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